Real-World Object Detection: Waste Sorting & Tomato Ripeness
Requirements
- Basic Python knowledge is helpful, but the course is beginner-friendly and guides you step-by-step.
- A computer with internet access and basic familiarity with running Python scripts.
- Interest in AI, computer vision, or sustainability-related projects.
Description
Are you ready to apply computer vision to real-world problems?
In this hands-on course, you’ll build two complete object detection projects: one for identifying household waste items (like plastic, glass, and paper), and another for detecting ripe and unripe tomatoes using the latest YOLOv10 model.
We’ll walk you through each step of the pipeline from dataset preparation and annotation to training and deploying your own AI models. You'll gain practical experience with tools like Annotate Lab, Gradio, and Ultralytics YOLO, while also learning how data augmentation and evaluation metrics can improve model performance.
Whether you're interested in sustainability, agriculture, or real-time AI applications, this course provides both the theory and implementation you need to bring AI to life.
By the end of this course, you will:
Train a YOLOv10 model to detect ripe vs. unripe tomatoes
Build an object detector for sorting waste categories
Annotate images using Annotate-Lab with YOLO format
Apply data augmentation to boost performance
Deploy your model using Gradio on Hugging Face Spaces
Export and run your model on mobile devices (optional module)
This course is ideal for:
Developers and data scientists curious about object detection
Environmental and agri-tech enthusiasts
Anyone looking to learn YOLOv10 with practical projects
Enroll today and build AI tools that make an impact from waste bins to tomato fields.
Who this course is for:
- Beginners and intermediate learners interested in applying computer vision to real-world problems.
- Developers, students, and enthusiasts looking to build practical AI projects in sustainability and agriculture.
- Educators and researchers interested in hands-on projects for waste detection and smart farming.
- Anyone curious about YOLO, object detection, or using AI for environmental impact.
Instructor
- 4.5 Instructor Rating
- 119 Reviews
- 5,910 Students
- 2 Courses
Suman has over 10 years of experience in the IT industry, specializing in AI and software engineering. He is the creator of D.Waste, an AI-powered platform for waste management. Suman has also developed a canvas game that integrates AI, which secured third place in the 2019 Developer Circles from Facebook Community Challenge in the Asia Pacific region.
Suman is the author of Learn JavaScript: Beginners Edition. Outside of his professional work, he is passionate about building developer tools to increase productivity and is dedicated to sustainable living and mountaineering.